GLBRC collaboration

Adina, Ashley, Nejc, Shane¶

1. MetaG Sequencing and alignment Summaries
   • Inputs:
     
     • 136 Phred-33 fastq files from samples obtained from washes of Switchgrass and Miscanthus transfered from JGI. Metadata
     • Illumina TruSeq version 3.2 sequencing adapters.
   • Outputs:
     
     • Adapter Trimming and QC (Trimmomatic) Report
       • The majority of reads are of high quality
     • Host Plant Alignment Report
       • ~80% of the reads at every time point align to the plant assembly. This tapers off toward the end of the season, likely because of the senescence of plant cells.
     • Fungal Alignments Report
       • Low fungal alignment. This may be due to having only a small number of fungal assemblies. The fungal reads in switchgrass peak at during the summer months at 9.1% of the remaining reads.
     • Metagenomic Assembly
       • 
       • Based on this overlap, we will go ahead and use the MAG assembly instead of the metagenomic assembly.
       • Method: Reads were trimmed, aligned to the host assembly, and reads with neither pair aligninging were extracted and aligned to the collection of fungal assemblies. All reads with neither pair aligned to the fungal assemblies were extracted again in "cleaned" fastq files. MegaHit was then used with the "--kmin-1pass" and "--presets meta-large" options to generate a metagenomic assembly.
     • MAG Assembly
       • The MAGs assembly was created by concatenating bins with $>=$ 50% commpleteness together into a single pseudo-assembly.
2. MetaG Analysis
   • Inputs:
     
     • The MAGs assembly
     • Functional Gene Count table, mapped to KEGG/functions using this annotation methodology. My script that follows these steps is here.
   • Research Questions:
     
     • What is the ordinal relationship between the samples' functional counts (PCoA)?
       • Primary access is time.
     • How do functional annotations accumulate over time?
       • The number of level 3 functional catagories consistently increases over time.
       • Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?
         • Yes for both crops on ('Time and Richness', 'Time and Shannon', Time and Pielou')
       • Do we see changes over time in functional richness?
         • Yes, primarily in catagories related to metabolism.
     • Is there a difference between treatment (Fertilized vs. Unfertilized)?
       • No statistically signficant signal detected.
     • Is there a difference between host plants?
       • Yes. $P-val = .027$
     • Is there similarity between the WGS communities and the 16S data?
       • Yes. Mantel statistic $r = .6526$

3. MetaT Sequencing and alignment Summaries

   • Inputs:
     
     • 74 Switchgrass samples and their respective fastq files. Metadata
     • Illumina TruSeq version 3.2 sequencing adapters.
   • Outputs:
     
     • Adapter Trimming and QC (Trimmomatic) Report
       • The majority of reads are of high quality
     • Alignment to the Switchgrass Assembly Report
       • The read alignment to the Switchgrass assembly is better (~50% of 2x reads compared to 80% of metaG reads).
     • Fungal Alignments
     • Alignment to the MAG assembly

4. MetaT Analysis

   • Next steps:

     1. Fix the metadata to ensure that each sample is accounted for and we have the seq files (Nejc)      ✓ Completed Wednesday, Feb 19,2020. Delivered by Kiera
     2. Modify the R analysis script to read results from the MetaT data (Nejc & Shane)
        

        In order for this to progress, 1 had to be complete. The next step is figure out why the metadata for the MetaT is not meshing with the R script. Nejcs was OOO last week but said that we could meet up this week.

     3. Explore the Kallisto output to determine how to extract annotations (Shane)
        

        Kallisto has an arguement to export a bam file when it runs, but I do not know how these bam files work or if they are the same thing as a bam from bowtie2. I am working with kallisto to get a bam file now and then I will see if that file works to extract annotations from the contigs

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MetaG Sequencing and Alignment Summaries

Full mapping script

Adapter Trimming and QC (Trimmomatic) Report

What is the abundance and quality of the reads in each sample?

Host Plant Alignment Report

When the reads are aligned to plant reference genomes, how many of the reads are plant-aligned reads?

Sequencing and alignment Summaries

Fungal Alignment Report

What reads are fungal reads?

Annotating the metagenomic assembly

Method: Reads were trimmed, aligned to the host assembly, and reads with neither pair aligninging were extracted and aligned to the collection of fungal assemblies. All reads with neither pair aligned to the fungal assemblies were extracted again in "cleaned" fastq files. MegaHit was then used with the "--kmin-1pass" and "--presets meta-large" options to generate a metagenomic assembly.

The annotations were performed using KEGG's prokaryotic peptides and eukaryotic peptides

Based on the high-overlap, we decided to use the mags instead of the assembly for alignment

MAG Stats¶

MetaG Analysis¶

PCoA

COG accumulation over time

Is time a factor that affects the functional richness of phylosphere communities (Alpha Diversity)?

Do we see changes over time in functional richness?

Call: adonis(formula = dist.otu ~ map_16S\$time_numeric)

Permutation: free Number of permutations: 999

Terms added sequentially (first to last)

Is there a difference between treatment (Fertilized vs. Unfertilized)?

Call: adonis(formula = dist.otu ~ map_16S\$treatment)

Permutation: free Number of permutations: 999

Terms added sequentially (first to last)

Is there a difference between host plant?

Call: adonis(formula = dist.otu ~ map_16S\$plant)

Permutation: free Number of permutations: 999

Terms added sequentially (first to last)

Is there similarity between the WGS communities and the 16S data (mantel/procrustes)?

Metatranscriptomic Sequencing

MetaT Sequencing and Alignment Summaries

Full mapping script

What is the abundance and quality of the reads in each sample?

How do the reads align to the Switchgrass assembly?

MetaT Analysis¶

Overarching analysis - changes in metagenome content over time

All bins with at least 50% completeness were used in a combined assembly. The analysis below comes from the counts for each sample. These counts were normalized by the number of reads that did not align to the fungal or host assemblies.

How do the reads align to the MAG assembly?

Outline

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